DOI: 10.1016/j.jag.2016.01.002
Scopus记录号: 2-s2.0-84988692289
论文题名: Multiscale quantification of urban composition from EO-1/Hyperion data using object-based spectral unmixing
作者: Zhang C
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 47 起始页码: 153
结束页码: 162
语种: 英语
英文关键词: EO-1/Hyperion
; Multiscale quantification
; Object-based MESMA
; Urban composition
Scopus关键词: aerial photography
; EOS
; Hyperion
; multispectral image
; pixel
; spatial resolution
; urban area
; urban planning
英文摘要: Quantification of the urban composition is important in urban planning and management. Previous research has primarily focused on unmixing medium-spatial resolution multispectral imagery using spectral mixture analysis (SMA) in order to estimate the abundance of urban components. For this study an object-based multiple endmember spectral mixture analysis (MESMA) approach was applied to unmix the 30-m Earth Observing-1 (EO-1)/Hyperion hyperspectral imagery. The abundance of two physical urban components (vegetation and impervious surface) was estimated and mapped at multiple scales and two defined geographic zones. The estimation results were validated by a reference dataset generated from fine spatial resolution aerial photography. The object-based MESMA approach was compared with its corresponding pixel-based one, and EO-1/Hyperion hyperspectral data was compared with the simulated EO-1/Advanced Land Imager (ALI) multispectral data in the unmixing modeling. The pros and cons of the object-based MESMA were evaluated. The result illustrates that the object-based MESMA is promising for unmixing the medium-spatial resolution hyperspectral imagery to quantify the urban composition, and it is an attractive alternative to the traditional pixel-based mixture analysis for various applications. © 2016 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80100
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Geosciences, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, United States
Recommended Citation:
Zhang C. Multiscale quantification of urban composition from EO-1/Hyperion data using object-based spectral unmixing[J]. International Journal of Applied Earth Observation and Geoinformation,2016-01-01,47